In response to the difficulty in identifying low-voltage AC series arc faults due to their particularity,an experimental platform is established in the laboratory to collect current waveform data of normal and arc faults under different loads.An adaptive neuro fuzzy inference system(ANFIS)fault arc detection method based on multi-information fusion and series is proposed.Through multi-level feature parameter extraction,ANFIS adaptive fuzzy neural network is trained and tested.The results show that this method can effectively overcome the shortcomings of slow convergence speed and large error precision in back propagation(BP)neural network fault diagnosis,and get more accurate and ideal diagnosis results,which opens up a new way for the research in this field.
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